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Samar Rahmouni

Samar Rahmouni

Master's Student in Computer Science Research

École Polytechnique, Paris

Research Focus

Formal Verification & Reinforcement Learning

"The future is neurosymbolic ——"

Languages

English, French, Arabic

Personal Interests

Dungeons & Dragons Philosophy Logic Puzzles Academic Writing

Industry

AI Engineer Intern

Faive @ Qatar

August 2026 - Present

Education

Master en Recherche Informatique

École Polytechnique, Paris

2023 - Present

Thesis: A Formal Development of Modal Logic IK in Coq (Labeled Sequent Calculus and Meta-theoretical Properties) This project presents a complete formalization of the labelled sequent calculus for intuitionistic modal logic (LabIK) in the Coq proof assistant. The system is then used to prove key meta-theoretical properties including admissibility of identity, weakening, invertibility and completeness with regards to intuitionistic modal logic (IK). View the Report.

Advised by Lutz Straßburger

Bachelor of Science in Computer Science

Carnegie Mellon University, Pittsburgh, PA

2018 - 2023

Honors Thesis: Domain Informed Oracle for Reinforcement Learning

Advised by Giselle Reis, Gianni Di Caro and Eduardo Feo Flushing

Concentration: Programming Languages

Research Projects

A Formal Development of Modal Logic IK in Coq

Partout - INRIA Saclay

March 2025 - Aug 2025

Formalization of the labelled sequent calculus for intuitionistic modal logic (LabIK) in the Coq proof assistant. We discuss different approaches and design choices made, precisely when it comes to representing the different contexts and the labels necessary for the system. We also discuss the challenges faced during the formalization and the limitations of our implementation.

Advised by Lutz Straßburger
Coq Formalization Intuitionistic Modal Logic

Proof Search in Pomset and BV logic

Partout - INRIA Saclay

Apr 2024 - Aug 2024

Implementation was done in OCaml while making use of the 'Logical' tool for the proof search of BV, specifically. Proof search in Pomset was implemented as the search of cycles on graphs: restricted to balanced formulas. The implementation in Pomset was used as a benchmark for testing the proof search on BV.

Advised by Lutz Straßburger
OCaml Proof Search BV Logic Pomset Logic

Proof Assistant for Categories encoded in an Equational Graphical Language

École Polytechnique, Paris

Sep 2023 - Jan 2024

Research on the link between equational and graphical structures. Transforming the categorical definition of a terminal object to an equational definition using the work done by Albert Burroni. Defined the relevant type system and its rules for terms, contexts and equalities.

Advised by Samuel Mimram
Agda Category Theory Graphical Algebra Type Systems

Domain Informed Oracle for Reinforcement Learning

Carnegie Mellon University

Sep 2021 - Dec 2022

Implemented a domain-informed module in ProgLog to guide the reward shaping of a Reinforcement Learning (RL) module. Independently gathered related work to better identify the problem of reward shaping in RL and investigate possible solutions. Adapted a deep-learning architecture to include a logic module, the model was formalized accordingly.

Advised by Giselle Reis Gianni Di Caro Eduardo Feo Flushing
Reinforcement Learning Logic Programming Reward Shaping Deep Learning

Proof Search and Certificates for Evidential Transactions

Carnegie Mellon University Qatar

Dec 2020 - Feb 2021

Provided a logical framework for distributed evidential transactions. Compiled relevant related work and proved cut-elimination for the logic (interesting proof found in annex of the paper).

Co-authors Vivek Nigam Giselle Reis Harald Ruess
Proof Theory Distributed Systems Cut Elimination Logic Frameworks

Behavioral Modulation of a Reinforcement Learning Controller using Artificial Emotions

Carnegie Mellon University Qatar

May 2020 - Sep 2020

Formalized and implemented a survival game scenario based on predators and preys. Action is determined by behavior and decision in the environment. Experimenting on outcomes of behavioral modulations and its learned effects on decisions.

Advised by Gianni Di Caro
Funded by QSIURP 2021
Reinforcement Learning Artificial Emotions Game Theory Behavioral Modeling

Get in Touch

Academic Collaboration

I'm always interested in discussing research opportunities, collaborations, or simply exchanging ideas about formal methods, AI, and the intersection of symbolic and neural approaches to computation.